A Holistic Approach to Information Processing for Biomedical Networks

描述(由申请人提供)： 申请者描述了一个为期5年的职业发展计划，在Marco Ramoni和他的共同导师David Bates、Isaac Kohane和Peter Szolovits的指导下，他在生物医学网络方面进行了独立的学术研究。申请者提出了一项培训和研究相结合的计划，以实现独立性。培训涉及申请者正在调查的网络的潜在生物医学方法。在研究方面，假设是生物医学网络中信息处理的整体方法能够发现通过当前的简化论方法无法识别的新型关系。目标是：1)设计和开发一个基于统计信号处理的方法论框架，能够分析 生物医学网络和发现隐藏的关系。2)开发和实施可扩展的模块化 能够自适应地将信息集成到目标1中描述的框架中的体系结构。3)将特定目标2中的体系结构应用于大规模基于eHR的临床信息学网络的分析系统的开发。

DESCRIPTION (provided by applicant): The applicant describes a 5-year career development program leading to independent academic research in biomedical networks under Marco Ramoni and co-mentors David Bates, Isaac Kohane, and Peter Szolovits. The applicant proposes a combined training and research program to lead to independence. Training involves biomedical methods underlying the networks being investigated by the applicant. On the research front, the hypothesis is that a holistic approach to the processing of information in biomedical networks is able to uncover novel types of relationships that could not be identified through current reductionistic methods. The aims are: 1) Design and develop a methodological framework, based on statistical signal processing, able to analyze biomedical networks and discover hidden relationships. 2) Develop and implement a scalable, modular architecture that is able to adaptively integrate information into the framework described in aim 1. 3) Apply the architecture in specific aim 2 to the development of a system for the analysis of large-scale EHR-based clinical informatics networks.